AI Green, Blue and Brown Belts cover in-depth the bases of machine learning and deep learning. These advanced AI Belts require an increasing level of difficulty and engagement leading you progressively to the AI Black Belt, truly a level of mastery.

Practical, real use cases

It will be hands-on! We will make it easy, by using code running in an open-source environment (Jupyter notebooks)

Even in the AI Orange Belt, designed for managers (non-coders), you will get to see the actual code running, be able to change parameters, and understand in some technical detail, really how AI works under the hood. You will learn a lot from interacting with your peers.

Finally, you will be exposed to real-world examples from practitioners such as Jetpack.ai, Sagacify, Radix.ai, etc.

Vendor-neutral, yet vendor-enabled.

Most of the environments and tools that we use are open source, to offer the most freedom. However, we intend also to enable learners to work with industry-standard environments in the cloud. There will be special sessions where learners will have a chance to experiment with the AI environments of the major providers:

Google Cloud

Amazon AWS

Microsoft Azure

IBM Watson

This will make sure that their skills are in sync with market expectation and geared towards production environments.

A community of learners

Once you start your journey with the AI White Belt, you will be part of the community of learners with a close relationship to our trainers, program designers, and practitioners, true AI experts in the field: Gilles Louppe (ULiège), Kevin Françoisse (Sagacify), Gregory Renard (xBrain), Gautier Krings (Jetpack.ai), and many others.

Because AI Black Belt relies very much on peer-learning, learners are expected to be open, and even to contribute to the community. For example, AI Green Belts are expected to mentor AI Yellow Belts, etc.

In addition to the classroom experience, there will be online resources (code repository, vidéos, playbook,...)